175 results about "Noise floor" patented technology

The invention relates to an adaptive noise floor energy detection method and system based on FFT frequency spectrum accumulation, and the method comprises the steps: carrying out the FFT frequency spectrum accumulation of an electromagnetic signal sampled by an ADC in an FPGA, and carrying out the channel division of a broadband frequency spectrum into sub-bands; counting and estimating the top and the bottom of the noise by sub-bands one by one; carrying out median filtering processing, subtraction and modular operation according to the obtained data to obtain optimal values of the energy bottom and the noise energy fluctuation range of each channel, carrying out summation to obtain a noise floor of each sub-band, and carrying out median filtering once to obtain a final noise floor value of each sub-band; and a noise factor is introduced to obtain a final adaptive constant false alarm threshold, and adaptive detection of noise floor energy is realized through the threshold. According to the invention, a parallel operation architecture based on the FPGA is adopted, so that the method is simple in calculation and high in sensitivity, and has the capability of detecting each sub-band signal at the same time.

The invention discloses a multi-bandwidth spectrum data signal adaptive extraction method based on a signal-to-noise ratio threshold, and relates to the technical field of spectrum signal extraction. The frequency spectrum data collection covers 30MHz-6GHz, the sampling rate is 20MHz, 16-bit quantization is realized, and the hardware fluctuation is eliminated through the dual-channel design; according to noise floor estimation, 50 frames of no-signal samples are taken, mean value calculation is carried out through a sliding window, then median filtering is carried out, and the noise power and confidence interval of each frequency point are obtained; basic values are set for a signal-to-noise ratio threshold according to frequency bands, dynamic adjustment is performed in combination with real-time noise standard deviation, and compensation is added to a known frequency band; for multi-bandwidth detection, wavelet packet decomposition is adapted to 100kHz-5MHz, candidate signals are marked when energy detection exceeds a threshold, and a range is determined by morphological filtering; extracting parameters such as center frequency, analyzing time-frequency characteristics through short-time Fourier transform, and calculating 4-order cumulants to establish feature vectors; coherent accumulation times are adjusted according to a signal-to-noise ratio, energy is superposed through phase alignment, and a purified signal is output through band-pass filtering. According to the invention, the signal detection precision and adaptability in a complex environment are improved, and misjudgment is reduced.

The invention discloses a self-adaptive large dynamic detection noise floor suppression system and a control method thereof. The system comprises a filtering selection front-end module, a detection synthesis module, a frequency measurement receiving module and an FPGA feedback control module. The method is composed of four main parts, namely a filtering selection front end, detection synthesis, frequency measurement receiving and FPGA feedback control. Wherein the filtering selection front end and the frequency measurement receiving end receive two groups of external radio frequency signals at the same time. And frequency measurement is carried out through a mature single-bit receiving scheme in frequency measurement receiving, and a result is sent to the feedback control module, so that switching of a filtering channel and suppression of a noise floor are realized. According to the invention, the broadband large dynamic DLVA detection sensitivity is obviously improved.

The invention provides a data processing and output circuit and method for a high-energy particle detection pixel sensor chip, and relates to the technical field of high-energy particle detection, and the method comprises the steps that each data processing unit receives ADC output of multiple channels, and carries out the validity discrimination of the received original data of each channel in a polling mode; effective case information in each data processing unit is summarized through a data integration circuit, and the effective case information is cached into a sparse signal output buffer; the data output interface circuit receives the information in the sparse signal output buffer, judges whether effective information needing to be output exists or not, and reads formatted data if the effective information exists. According to the invention, the output signal of the quantization circuit is discriminated so as to distinguish an effective case and a noise background, only pixel data containing an effective particle hit event is subjected to position correlation and coding, pixels not containing the effective hit event are skipped, and whether the data output interface outputs data to the outside is determined according to whether the effective case exists or not.

The invention provides a radar signal adaptive threshold generation method, which comprises the following steps of: when a threshold is generated, assigning a lower limit of a received system binding threshold as a current threshold value; opening a time window with the point number of M, and counting the time window with the point number of M: counting every M points as a counting period, and recording instantaneous amplitude values of a plurality of points in the time window in one counting period; if the instantaneous amplitude values of the majority of points in the time window do not exceed the current threshold, increasing the current threshold on the basis of the current threshold; if the instantaneous amplitude values of the majority of points in the time window exceed the current threshold and 1.25 times of the average level of the noise floor exceeds the current threshold, the current threshold is increased on the basis of the current threshold; and when 1.25 times of the average level of the noise floor is lower than the current threshold, the current threshold is lowered. The invention further provides a computer readable storage medium which is used for realizing the radar signal adaptive threshold generation method.

A system that performs beam selection and beam merging using beam-specific signal quality metrics corresponding to a minimum noise floor. For example, a device may track a minimum noise floor for each beam, determine a highest minimum noise floor across the beams, and determine a noise floor ratio between the beam-specific minimum noise floor and the highest minimum noise floor. Using a combination of the noise floor ratio and signal-to-noise ratio (SNR) values, the device may perform beam selection by prioritizing low background noise as well as high SNR to select a pre-defined beam group. In addition, the device may use the noise floor ratio to perform beam merging and generate single-channel output audio data using the selected beam group. For example, the device may scale the beams based on a combination of the SNR value and the noise floor ratio.

The invention relates to the technical field of low-power-consumption electronics, and discloses a low-power-consumption instantaneous frequency measurement system which comprises a radio-frequency signal acquisition module, a signal time-frequency conversion module, a noise floor coding module and the like. The system generates a feature tensor through time-frequency analysis of a radio frequency signal, realizes dynamic threshold fusion in combination with noise floor sparse coding, extracts a multi-scale transient frequency feature by using a pyramid convolutional neural network, dynamically suppresses noise based on a signal-to-noise ratio weight, and reconstructs a real-time spectrum distribution image. The power consumption control module can adjust the ADC sampling rate and the clock frequency of the processing unit according to the signal strength, and the power management unit adopts multi-voltage domain independent power supply. The system solves the problems of frequency measurement precision and power consumption under complex noise, is suitable for the fields of wireless communication and the like, and has the characteristics of high precision, low power consumption, high spectral resolution, visualization and intuition.

A method of determining a location of a mobile device in the presence of a spoofing signal includes receiving a GNSS signal and detecting a spoofing condition based on a signal strength of the GNSS signal. The spoofing condition may comprise an increase in the signal strength, the signal strength exceeding a threshold value, an increase in a noise floor related to a measurement of the signal strength, or a combination thereof. The method may further comprise, responsive to detecting the spoofing condition, providing an indication of the GNSS signal as a spoofing signal.

The invention relates to the technical field of optical fiber sensing signal processing, in particular to a DAS signal floor noise elimination method, system and equipment based on statistical analysis, and the method comprises the steps: initializing system parameters, and loading a DAS application field data matrix; performing slicing and frequency domain transformation on the DAS original data; dynamically determining a peak threshold value, and performing adaptive peak searching according to the peak threshold value; sorting the identified and screened local maximum values in a descending order, and selecting frequencies corresponding to the local maximum values as main frequency candidates; performing clustering analysis on the selected dominant frequency candidates; calculating the cumulative proportion of each main frequency in the total statistics, selecting a center frequency, and forming the multi-frequency band elimination of the monitoring unit by using band elimination frequency bands formed by different center frequencies; and adding the multi-frequency band elimination to a statistical filtering frequency band set of all the point locations, storing the statistical filtering frequency band set of all the point locations as a statistical model, and performing background noise elimination on the DAS original signal based on the statistical model.

The invention discloses a vibration sensor background noise testing method based on a vacuum cavity, and the method comprises the steps: constructing an active-passive composite vibration isolation platform in a sealed vacuum cavity, rigidly fixing a to-be-tested sensor on the vibration isolation platform in a testing process, and guaranteeing that a sensitive axis of the to-be-tested sensor is orthogonal to a cavity reference; and an output signal is recorded for a long time at a sampling rate greater than or equal to 256Hz through a high-precision acquisition system. The data processing comprises polynomial detrending, sliding window de-averaging, multi-band elimination filtering and power spectral density (PSD) analysis so as to extract the equivalent amplitude and frequency domain characteristics of the background noise. In order to ensure the credibility of the result, the test needs to be repeated for three times, the consistency of the PSD curve is compared, and the deviation does not exceed 5%. The method combines the vacuum environment, composite vibration isolation, signal preprocessing and spectrum analysis technologies, can accurately quantify the background noise characteristics of the sensor, and is suitable for research and development verification and performance evaluation of the high-sensitivity sensor.

The invention discloses an optimal linear point searching method for a silicon-based Mach-Zehnder modulator. According to the method, the linearity of a corresponding working point is estimated according to the power of a fundamental component and a third-order intermodulation component of an output signal of the modulator, and the optimal linear point of the modulator can be obtained based on the maximum estimated value of the linearity. According to the method, a maximum entropy spectral subtraction method is adopted to reduce a signal noise floor, and a violent search method is adopted to retrieve an optimal combination of a modulator upper and lower arm phase difference and a reverse bias voltage to obtain an optimal working point. Compared with a conventional linearity test method that the linearity is obtained by testing when the working point of the modulator is set to be an orthogonal point, the optimal linear point searched by the method can obviously improve the linearity of the modulator, and a high-linearity silicon-based integrated microwave photon system can be realized.

The invention discloses a network signal interference detection system based on spectrum analysis. The system comprises a network signal acquisition module, a spectrum preprocessing module, a spectrum calculation module, a frequency separation spectrum kurtosis analysis module, a Bayesian online change point detection module, a parameter linkage module, an interference discrimination module and a result output module. The frequency separation spectrum kurtosis analysis module outputs kurtosis statistics and noise bottom estimation according to time slices based on the power spectrum; the Bayesian online change point detection module updates and outputs the change point position, the confidence coefficient and the adaptive time window parameter online; the parameter linkage module updates the frequency separation spectrum kurtosis analysis module according to the data; and the interference judgment module generates an interference event list, and the result output module outputs alarm and troubleshooting positioning data. According to the invention, automatic detection and discrimination of same-frequency superposition, adjacent-frequency superposition, burst intermittence and noise bottom uplift interference are realized, the accuracy is improved, and the troubleshooting cost is reduced.

The present invention discloses a base station construction plan guidance method, device and storage medium, the method comprising: determining a first test result that meets a first requirement by adjusting the isolation distance between a first node and a second node; the first requirement comprising: a noise floor rise value of the second node being a first target value; the first test result comprising: a first isolation distance between the first node and the second node; determining a second test result that meets a second requirement by adjusting the transmission power of the first node; the second requirement comprising: a noise floor rise value of the second node being a second target value; the second test result comprising: the transmission power of the first node; and determining a target isolation distance and / or a target noise floor rise value under a target rate requirement based on the first test result and the second test result.

This application discloses a wind tunnel-based noise detection method, apparatus, storage medium, and electronic device. The method includes: when testing a test piece in a wind tunnel, acquiring a measured noise spectrum in the testing environment and obtaining the operating frequency of the wind tunnel's inverter; matching the background noise spectrum corresponding to the operating frequency in a background noise spectrum library based on the operating frequency; aligning and dividing the measured noise spectrum and the background noise spectrum using a frequency band division rule adapted to the inverter's operating frequency to obtain multiple frequency band units; based on the acoustic energy density of the measured noise spectrum and the background noise spectrum within each frequency band unit, extracting the energy component corresponding to the background noise spectrum from the measured noise spectrum through directional orthogonal projection, and reconstructing the spectrum of the residual energy after extraction to obtain the effective aerodynamic noise spectrum of the test piece; and calculating the noise detection result of the test piece based on the effective aerodynamic noise spectrum.

A wireless device is configured to transmit radar signals at extremely low spectral density so that the receiver can be operated at the same time without saturating and thereby enabling full-duplex operation. To achieve sufficient range, beamforming is used together with a very long correlation time for detection of the radar signal, in which case the receiver can resolve backscattered or reflected radar signals far below the noise floor, while the bandwidth of the transmitted radar signal can be very high. The wide bandwidth enables the wireless device to maintain a low power spectral density while increasing output power, and also increase the depth resolution. The extremely low power spectral density even in the transmission beam direction makes the probability that communication will be disturbed very low. The high bandwidth calls for digital filters for both transmitted and received signals to equalize the radar frequency response characteristics of the radio unit.

Systems and methods for a MEMS microphone package are disclosed. The MEMS microphone package may include a first port to direct sound to a MEMS system, including a die substrate, an acoustic membrane, and one or more plates. The MEMS microphone package may include an ASIC to produce microphone output based on an electrical signal, a PCB, a lid, and a second port. The first port and the second port may define a front volume and a back volume respectively. The second port may increase the back volume to improve sensitivity and reduce the acoustic sensor's noise floor to improve signal-to-noise ratio.

[Problem] To provide a determination device, a determination method, a determination program, and a radar device for determining the presence or absence of radio wave interference that does not cause a noise floor rise even when there is radio wave interference and does not require a special pattern provided for radio wave interference. [Solution] A determination device according to one embodiment of the present technology is provided with a reception unit and a determination processing unit. The receiving unit receives a first reflected chirp signal generated by a first transmission chirp signal transmitted toward an object by a transmitting device and reflected from the object, and a second reflected chirp signal generated by a second transmission chirp signal transmitted by the transmitting device at a time different from a time at which the first transmission chirp signal is transmitted and reflected from the object. A determination processing unit compares a plurality of arrival angle spectrums generated based on a plurality of corrected signals obtained by performing a plurality of velocity aliasing correction processes on the first reflected chirp signal and the second reflected chirp signal, and determines whether or not a useless signal is received.

This invention discloses a magnetotelluric denoising method and system based on a physics-driven and conditional diffusion model, belonging to the field of electromagnetic signal processing technology. This method integrates the advantages of neural networks and the physical characteristics of magnetotelluric signals, and proposes a physics-driven synthesis strategy based on statistical priors of measured source data and a curriculum-based dynamic physics-driven noise addition strategy based on training progress factors. Addressing the scarcity of high-quality, clean samples, a clean background field that highly approximates real physical characteristics is synthesized using a parametric mathematical model. The introduction of curriculum-based dynamic physics-driven noise addition (such as noise floor annealing, square wave incrementing, and morphological clustering pulses) accurately simulates natural background degradation and complex human interference, enabling the model to adapt to extremely complex time-frequency characteristics under different geological structural backgrounds. This completely overcomes the domain shift problem caused by static Gaussian white noise training, constructs a richer sample library, and lays the foundation for accurate denoising of conditional diffusion models.

The present disclosure relates to an audio processing method and device, electronic equipment and storage medium, the method comprising: converting an audio signal of a target audio device collected to a frequency domain to obtain first frequency domain information of the audio signal; wherein the first frequency domain information comprises amplitude values of different frequency components of the audio signal; determining a reference value according to the amplitude values; determining noise floor information of the audio signal according to differences between the amplitude values of different frequency components and the reference value; and the noise floor information is used to reflect a noise floor processing capability of the target audio device.

This application discloses a method and product for self-diagnosing external interference. The method includes: acquiring the inherent parameters of the frequency-using terminal to calculate the theoretical noise floor; measuring the total received power in real time and calculating the super-noise power accordingly; when the super-noise power exceeds a preset power threshold, acquiring the baseband demodulation quality parameters of the current channel; and performing correlation discrimination based on the super-noise power and baseband demodulation quality parameters. When the super-noise power is high and the demodulation quality is below a preset threshold, it is determined to be external interference; otherwise, it is determined to be a strong useful signal. This application establishes a two-dimensional causal correlation model between physical layer power and baseband layer quality within the terminal, enabling real-time and objective self-diagnosis of external interference from the terminal's own perspective, thus improving the objectivity, timeliness, and accuracy of the diagnosis.

The invention relates to the field of noise elimination, in particular to a method, a medium and equipment for eliminating FSK noise in a cockpit voice record. Comprising the following steps: determining whether an FSK noise section and a reference audio section on a to-be-processed recorded audio are background noise or not; if the FSK noise section and the reference audio section are both non-background noise, the frequency domain similarity between the first discriminant audio and the first reference audio is greater than a first similarity threshold, and the time domain similarity between the first discriminant audio and the first reference audio is greater than a second similarity threshold, determining that the first discriminant audio and the first reference audio are not background noise; if so, the audio of the FSK noise segment is replaced with the audio in the reference audio segment. According to the method, the characteristics of CVR multi-channel recording are utilized, the audio similarity of two microphone channels is compared, noise is eliminated in an automatic mode, the method is suitable for rapidly processing single or multiple records, and the cabin sound analysis efficiency is improved.

Background noise estimation and noise reduction are disclosed, in an embodiment, a method includes: obtaining an audio signal; dividing the audio signal into a plurality of buffers; determining time-frequency samples of each buffer of the audio signal; determining, for each buffer and each frequency, a median (or mean) of energies and a measure of energy variation based on samples in the buffer and samples in adjacent buffers, the samples in the buffer and the samples in the adjacent buffers together spanning a specified time range of the audio signal; combining the median (or mean) of energies and the measure of energy variation into a cost function; for each frequency: determining a signal energy of a particular buffer of the audio signal corresponding to a minimum of the cost function; selecting the signal energy as an estimated background noise of the audio signal; and using the estimated background noise to reduce noise in the audio signal.

The invention discloses an optical fiber array coupling system and method based on multi-source data fusion, and relates to the technical field of optical fiber array coupling system.When an automatic coupling machine receives a working instruction, the system firstly starts a pre-coupling process of an optical fiber array, fuses and analyzes multi-source vibration state data, corrects operating parameters in real time, effectively suppresses initial mechanical artifacts, and finally, the optical fiber array is subjected to multi-source data fusion analysis; the adaptability of equipment to external disturbance and signal ground noise is improved, after initialization of operation parameters is completed, the system enters an actual coupling process, key working condition parameters are continuously monitored, and whether further optimization and adjustment are needed or not is dynamically judged, so that the mechanical vibration amplitude and response dispersion in the coupling process are reduced, and the coupling efficiency is improved. According to the optical fiber array coupling detection system, signal bottom noise and mechanical artifact superposition amplification are prevented, the signal quality and the structural stability are improved, when it is detected that an optical fiber array completes coupling, the system executes locking and steady-state processing according to a preset sequence, and the connection anti-interference performance and the long-term stability are improved through technological solidification and closed-loop parameter adjustment.

Systems and methods of in-sync / out-of-sync (IS / OOS) determination in the unlicensed band are described. Reference signals are measured on the unlicensed band. If the UE determines that at least one of the reference signals is missing, the IS / OOS condition is evaluated on that basis. If the missing signals are ignored when determining the IS / OOS condition, and the IS / OOS condition is unable to evaluated, the L1 sends an indication to the RRC layer. If the number of indications exceeds a threshold, the UE performs re-establishment or sends a report to the base station for adjustment of the reference signal resources. If the missing signals are counted, the missing signals are weighted based on proximity to the noise floor or a number of adjacent signals that are missing.

The invention provides a vehicle-mounted antenna floor noise testing method, device and equipment and a storage medium, a vehicle-mounted antenna is connected to a first port of a three-way connector, a vehicle-mounted receiver is connected to a second port of the three-way connector, and the testing equipment is connected to a third port of the three-way connector. Determining a power spectrum corresponding to the output signal; according to the power frequency spectrum corresponding to the output signal, an equivalent noise broadband corresponding to the vehicle-mounted antenna is determined, and the equivalent noise broadband is used for measuring the anti-interference capability of the vehicle-mounted antenna to environmental noise. As the original access of the vehicle-mounted antenna and the vehicle-mounted receiver does not need to be disconnected, the connector does not need to be repeatedly plugged, the signal acquisition of the vehicle-mounted antenna is realized on the premise of not influencing the normal work of the original vehicle system, and meanwhile, the problem of noise introduction caused by repeatedly plugging the connector is avoided; and the test precision of the floor noise of the vehicle-mounted antenna is improved to a certain extent.

This invention relates to a method for estimating the noise floor of a two-dimensional R-V spectrum based on moving averages. This method is used to process radar echo signals to obtain the noise floor. The radar echo signal is a three-dimensional spectrum, with its three dimensions corresponding to the range index R, the Doppler velocity index V, and the signal amplitude Am under the (R,V) index. The estimation method involves traversing all (R,V) values ​​of the radar echo signal and calculating the noise floor using a two-dimensional moving average method during the traversal. This invention uses a cross-shaped two-dimensional moving average method to estimate the noise floor, increasing the noise floor calculation sample from one-dimensional to two-dimensional. The calculated noise floor is more stable and closer to the true noise floor of the R-V spectrum.

The application discloses a kind of self-adapting transfer function equalization vector sensor background noise measurement method and system, belong to underwater acoustic sensor technical field.The output signal of the vector sensor to be measured and the reference signal of reference sensor are obtained;Based on the reference signal input to adaptive filter, the weight coefficient of adaptive filter is dynamically updated by adaptive algorithm, to establish the time-varying transfer function model from reference sensor to the sensor to be measured;Based on time-varying transfer function model, the reference signal is processed, and the result that input signal is transferred to the sensor to be measured by reference sensor transfer function compensation is obtained;The output signal of the vector sensor to be measured and the compensated signal are input into DHCM algorithm, and the background noise estimation of the sensor to be measured is obtained.The application is used to solve the problem that indirect measurement algorithm for different sensors will be distorted, aims at effectively improving the accuracy and environmental adaptability of low-frequency band background noise measurement.

The present invention discloses a full-duplex digital domain self-interference cancellation method, belonging to the field of wireless communications. The method utilizes the correlation between cached transmit symbol sequences and received symbol sequences to perform precise self-interference channel estimation, thereby improving channel estimation accuracy. The high-precision self-interference channel estimation result is applied to digital domain self-interference signal reconstruction. The reconstructed digital domain self-interference signal is subtracted from the received signal to complete digital domain self-interference cancellation. The method can achieve self-interference cancellation results below the noise floor and, through multipath cascading, can further be used for self-interference cancellation under multipath conditions.

This invention belongs to the field of noise floor reduction and proposes a frequency-band noise floor reduction method based on a spectrum analyzer. This invention can solve the problems of uneven noise power distribution and excessive noise power estimation. It includes the following steps: acquiring the noise floor signal of the spectrum analyzer, wherein the noise floor signal is a low-pass or band-limited white noise signal with a specified bandwidth; dividing the specified bandwidth into a first number of sub-segments and dividing the signal power before denoising into a first number of sub-segments; estimating the noise power under the specified bandwidth and dividing it into a first number of sub-segments; denoising each sub-segment and calculating the noise power spectral density of each sub-segment after denoising based on the bandwidth after segmentation, the signal power before denoising after segmentation, and the estimated noise power after segmentation; and ensuring that the noise power spectral density after denoising is not negative by using the compression factor method or the square root method.

The application relates to a dual cascade flow type processing method and system for removing artifacts from myoelectric signals and reconstructing the signals, and relates to the technical field of biomedical signal processing.The method comprises the following steps: extracting a standard stimulation artifact template from a noisy calibration myoelectric signal, calculating a decision threshold and a frequency domain noise floor baseline; transversely splicing a myoelectric signal data block with historical data in a time domain residual artifact cache, and performing artifact identification and cancellation based on the standard stimulation artifact template and a morphological gating mechanism; sending a time domain processing signal into a frequency domain splicing cache, performing fast Fourier transform after reaching a preset window length; dynamically generating a probability mask according to the frequency domain noise floor baseline, performing inverse fast Fourier transform, and obtaining a single-frame recovered signal; and obtaining a smooth and continuous reconstructed myoelectric signal by using an overlap-add method; and on the premise of not depending on high-performance hardware, accurate cancellation of stimulation artifacts is realized, and real physiological signals are protected.